Estimates are critical to most, if not all, businesses. Despite the critical nature of estimates, most of the techniques in use do not give good results. As a result, we jeopardize schedules, profits, customer relationships, and employee morale far too frequently. Why are our estimates so bad?<br /> Many of the estimates that we rely upon are generated by using “average” assumptions to give expected outcomes. Average inputs should give average results, right? Wrong! In almost any system of reasonable complexity, average inputs will not generate average outputs. As a result, many of our estimates are overly optimistic and hence overly risky. Even in those rare situations where average inputs do generate average results, the actual outcome will almost never be at the average that was estimated. Therefore, it is critical for good decision making to generate estimates that include a view of the likely variability of the outcome. Decisions made without knowledge of likely variability are inherently risky and doomed to fail.